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Proposed London
Low Emission Zone
Impacts Monitoring Programme
Charles Buckingham
Monitoring Manager
Transport for London
Background
• Proposed scheme being taken forward by TfLCongestion Charging Division
• History of CC Monitoring and Annual Reports
• Monitoring Strategy for Low Emission Zone
• But a quite different scheme requiring appropriate monitoring
• Purpose: Give an overview of the LEZ Monitoring Strategy
Projected air quality impacts
� 2008 proposals (HGVs, buses & coaches Euro III for PM) would reduce area of London exceeding:
- annual mean PM10 objective by some 5.8%- daily mean PM10 objective by some 7.4%- annual mean NO2 objective by some 5.2%
� 2012 proposals (HGVs, buses & coaches Euro IV for PM & heavier LGVs & minibuses at Euro III) would reduce area of London exceeding:
- annual mean PM10 objective by some 16.2%- 24 hour mean PM10 objective by some 14.7%- annual mean NO2 objective by some 15.6%
Distinguishing challenges
• LEZ impacts small in measurement terms (but important) and evolutionary
• Other things going on at the same time
• No ‘visible’ effects on traffic volumes or flows (i.e. affects vehicle population composition)
• Key out-turn objectives (e.g. health benefits) can’t be readily measured
• Detection/expression of impact dependent on exogenous factors (weather, smoking ban)
• Many AQ relationships/science poorly understood, unlike traffic,where basic relationships well understood.
Impacts hierarchy
• Level 1: Vehicle population change (Obs)
• Level 2: Resulting changed emissions (Calc)
• Level 3: Resulting changed air quality (Calc/Obs)
• Level 4: Consequences of changed air quality (Est)
• Other: Economic impact of scheme (incl. operator
behaviour)
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Approach
• Ensure robust measurement of vehicle population change
• Use this to calculate emissions change via LAEI
• Use this to calculate AQ change via AQ model
• Compare resultant changes with observed AQ data
• Use best assessment of attributable change to estimate
consequent changes in, for example, health
• Separate work stream for economic/business issues
• Supporting scientific development where appropriate
Vehicle population change
• Network of ANPR cameras (c. 100)
• Representative sample, stratified (33 strata)
• Match with supplemented DVLA database (Euro
Class)
• 4 weekly rolling indicators of population composition
for ALL vehicle types (4+ wheels)
• Now in place and generating data
• Output directly compatible with LAEI
ANPR ‘Spike’ cameras
Cumulative unique vehicle captures
– very early and provisional data
Concept – Euro Class tracking –
very early and provisional data
London vehicle fleet - Cars
Some initial comparisons
0%
5%
10%
15%
20%
25%
30%
35%
40%
45%
Pre-Euro I Euro I Euro II Euro III Euro IV Euro V
Euro Class
% of observations
camera captures
national fleet
LAEI
Estimating emissions change
• Updated LAEI baseline for 2006 (from 2004)
• ‘Do nothing’ 2007
• LEZ case(s) 2007 - 3, 6, 12 months on
• Repeated for subsequent LEZ horizons
• Calculate changed contribution from RT and LEZ affected vehicles for
PM, NOx/NO2 (attribution)
• Necessary LAEI enhancements: emissions factors, primary NO2,
PM10/2.5
• Important by-product: observed measurements of London specific
vehicle fleet characteristics
Reductions in concentration of PM10
in 2008
Reductions in concentrations of NO2
in 2012
Calculating air quality change
• Use emissions scenarios as input to AQ model.
• Output concentrations under static meteorology provide indicators of
change.
• Attribution possible from emissions datasets.
• Necessary model enhancements: NOx chemistry, PM
dispersion/reactivity by size and source.
• Compare model outputs with observed concentrations.
• Therefore, good (calculated) estimate of AQ change due to LEZ.
• Basis for estimation of ‘consequent’ impacts, e.g. on health.
Reduction in the number of people exposed to
PM10 levels above the limit value in 2008
Measuring air quality change
• Paradox – first point of reference but least likely to
demonstrate clear short term effects.
• LAQN – established (but TEOM problem and little PM
speciation).
• LEZ (‘Supersites’) – primarily to understand relationships
between traffic, pollutants and PM species at micro scale at
high LEZ ‘signal’ sites => feed into inventory/model
development and assist interpretation (Ben).
• Range of possible ‘outcomes’ for medium-term observed
concentration trends.
Consequences of air quality change
• AQ Objective compliance.
• Health improvement – not amenable to direct measurement
hence re-calibrate forecast model with observed AQ impacts.
• But first need to verify that existing method adequately reflects
expression of observed AQ impacts (e.g. differential impact by
PM size).
• Wider environment/amenity – again not amenable to direct
measurement.
• Secondary gains – e.g. potentially noise, CO2, other pollutants
(by product of PM abatement): exploratory studies.
Economic Impacts
• LEZ accelerating an established process, ‘bringing forward’
a component of change that would in any case happen.
• Several complex effects around operator strategies and
vehicle turnover (additional costs ‘brought forward’).
• Observed vehicle change dimensions scale of impact.
• 2 key elements: deviation from established trends across a
range of indicators (largely 3rd party data), and an ongoing
survey of operator behaviour.
• Potential +ve and –ve effects, widely spread.
Outside London
• Significant AQ benefits outside London.
• But prohibitive to measure in detail.
• NAEI framework using calculated UK/International fleet changes with sample measurements on UK motorways.
• Corresponding calculated emissions/AQ/health impacts assessment.
• Economy – London hauliers based country wide & abroad.
Developing the science
• London vehicle population => new baseline estimates
• PM characterisation (emissions, components)
• Secondary effects of PM abatement (e.g. primary NO2)
• Health impact pathways (how does PM change affect
health) – KCL work
• Intra-site relationships between traffic and pollutants
• Not going to solve all problems - but should realise useful,
targeted improvements to methods
